{"id":"W3041741830","doi":"10.24963/ijcai.2020/664","title":"Bidirectional Heuristic Search: Expanding Nodes by a Lower Bound","year":2020,"lang":"en","type":"article","venue":"","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Israel Science Foundation; Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research; National Science Foundation","keywords":"Heuristics; Upper and lower bounds; Computer science; Heuristic; Mathematical optimization; Branch and bound; Bidirectional search; Algorithm; Search algorithm; Theoretical computer science; Best-first search; Beam search; Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002473312,0.001198838,0.001283952,0.00176902,0.0007988506,0.001660257,0.002202582,0.001827881,0.006437843],"category_scores_gemma":[0.01133718,0.000778528,0.0008588024,0.001768023,0.001390423,0.002670691,0.002843694,0.002288667,0.001097998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001310902,"about_ca_system_score_gemma":0.002247356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00449223,"about_ca_topic_score_gemma":0.005625254,"domain_scores_codex":[0.9980832,0.0007332169,0.00006499334,0.0002244261,0.0006235134,0.0002707602],"domain_scores_gemma":[0.9957579,0.002911528,0.000231738,0.0004654357,0.0004585975,0.000174897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004218909,0.0003677447,0.001772796,0.0004360268,0.00009630519,0.0001699838,0.0003541652,0.5004857,0.009388986,0.1742049,0.01044615,0.3018554],"study_design_scores_gemma":[0.0000647402,0.00008544428,0.0001698943,0.00008086454,0.00003605872,0.00005438674,0.00006083091,0.9368045,0.002938405,0.05338587,0.006299602,0.00001952878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.022043,0.0005026722,0.9653628,0.0004541244,0.00007200259,0.0001555281,0.0001076764,0.0006903206,0.0106119],"genre_scores_gemma":[0.2344882,0.0004289115,0.7582687,0.0004382127,0.00007246429,0.0004519073,0.0003500599,0.0004111907,0.00509034],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006437843,"threshold_uncertainty_score":0.02153671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03374550677601711,"score_gpt":0.2613294497068696,"score_spread":0.2275839429308525,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}